• DocumentCode
    2570577
  • Title

    An application of wavelet transform and adaptive filters for decomposition of the HRV signals in the case of patients with coronary artery disease

  • Author

    Tkacz, Ewaryst ; Kostka, Pawel ; Komorowski, Dariusz

  • Author_Institution
    Found. of Cardiac Surg. Dev., Inst. of the Heart Prothesis, Zabrze, Poland
  • Volume
    6
  • fYear
    1998
  • fDate
    29 Oct-1 Nov 1998
  • Firstpage
    3120
  • Abstract
    The main aim of the paper is to present a new approach to the effective decomposition of HRV signals with the help of both the wavelet transform and adaptive filters. Several steps describing the process of HRV decomposition are presented. The major goal of the work is to obtain a method which allows completely noninvasive distinguishing of the patients with different levels of coronary artery disease. Previously applied methods were either invasive or inaccurate, especially due to an inappropriate HRV signal model. This model was often a cause of errors leading to misinterpretation or even bad classification of the particular patient
  • Keywords
    adaptive filters; deconvolution; electrocardiography; medical signal processing; signal classification; signal representation; wavelet transforms; ECG; HRV signals decomposition; Hilbert transform; MSE; adaptive filters; coronary artery disease patients; deconvolution; signal representation; wavelet transform; Adaptive filters; Continuous wavelet transforms; Coronary arteriosclerosis; Data mining; Fourier transforms; Frequency; Heart rate variability; Signal analysis; Wavelet analysis; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE
  • Conference_Location
    Hong Kong
  • ISSN
    1094-687X
  • Print_ISBN
    0-7803-5164-9
  • Type

    conf

  • DOI
    10.1109/IEMBS.1998.746153
  • Filename
    746153